diff --git a/las_outputs.py b/las_outputs.py
index a389466..cd6982f 100644
--- a/las_outputs.py
+++ b/las_outputs.py
@@ -180,25 +180,21 @@ for i, row in params_file.iterrows():
     # Crop point cloud to swash boundary
     las_data = call_lastools('lasclip', input=input_las, output='-stdout',
                              args=['-poly', crop_swash_poly], verbose=False)
-    # crop_las(input_las5, crop_swash_poly, final_las, path_2_lastools)
 
     # Apply sea-side clipping polygon
     las_data = call_lastools('lasclip', input=las_data, output='-stdout',
                              args=['-poly', crop_heatmap_poly], verbose=False)
-    # crop_las(final_las, heatmap_crop_poly, heatmap_las, path_2_lastools)
 
     # Create clipping polygon for heatmap raster
     shp_name = os.path.join(output_poly_dir, las_basename + '.shp')
     call_lastools('lasboundary', input=las_data, output=shp_name, verbose=False)
-    # las_boundary(heatmap_las, output_poly_name, output_poly_dir, path_2_lastools, zone_MGA)
 
-    #make a raster
-    # make_raster(heatmap_las, output_raster, path_2_lastools, keep_only_ground=True)
+    # Make a raster from point cloud
     tif_name = os.path.join(output_tif_dir, las_basename + '.tif')
     call_lastools('blast2dem', input=las_data, output=tif_name,
                   args=['-step', 0.2], verbose=False)
 
-    #extract the points and get volumes
+    # Extract elevations along profiles from triangulated surface
     df = extract_pts(
         las_data,
         cp_csv,
@@ -216,10 +212,8 @@ for i, row in params_file.iterrows():
     for profile_name in profile_names:
         plot_profiles(profile_name, survey_date, csv_output_dir, graph_loc, ch_limits)
 
-
-    #delete the temp files from the tmp_dir and the interim_dir
+    # Remove temprary files
     remove_temp_files(tmp_dir)
-    #remove_temp_files(int_dir)
 
 print("doing the volume analysis")
 # test=profile_plots_volume(csv_output_dir, profile_limit_file, volume_output, graph_loc)